Vertical sound localization in left, median and right lateral planes
Bibliographic record
Abstract
A few studies have reported better auditory localization under binaural listening for sounds presented from the left side of midline compared to the right. That asymmetry was attributed to a superior ability to resolve front/back confusions in the left hemifield. This research further investigated asymmetric effects in an experiment assessing vertical localization in three lateral planes perpendicular to the interaural axis (median, left and right). Eleven sources spaced at 18-deg intervals were arrayed around the upper half of the cone-of-confusion intersection in each plane. Subjects (15 males, 9 females) were required to identify the direction of incidence of a 250-ms band-limited white noise stimulus (250-8000 Hz). Statistical analyses performed on the proportion of correct responses and on three different angular error measures did not uncover any significant effect in performance for sources on the left versus right side of subjects. However, significant gender differences favoring male subjects were found for the variable and total error measures. This finding may be a purely physical effect due to the smaller size of female ears on average or related to cognitive effects. Results must be viewed in light of the wide distribution of response patterns from subject to subject; while most responded symmetrically and over the entire localization array, some had distinctive asymmetrical behaviors and/or systematic response biases in specific sectors of the localization array.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".